For all our experiments we used a weighted cross-entropy loss and trained MKIS-Net using adaptive moment estimation (Adam) optimization [1]} with an initial learning rate of 0.001 and an exponential decay rate of 0.9. The maximum number of iterations during the training phase was set to 10. Note that different methods can be used for assigning loss weights. The method of median frequency balance was utilized here for the calculation of class association weights [2]}.
